Vertical farming systems and methods

ABSTRACT

An automatic vertical farming system may include a frame defining at least one growth area and configured to support a plurality of vertical plant growth structures within the at least one growth area. The system may include at least one light, at least one liquid conduit, and at least one gas conduit. The system may include at least one robot disposed on a top side of the frame and movably supported by the frame. The at least one robot may include at least one tool configured to manipulate the plurality of vertical plant growth structures. The system may include a control system including at least one processor configured to automatically control illumination by the at least one light, liquid flow through the at least one liquid conduit, gas flow through the at least one gas conduit, and operation of the at least one robot.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/206,681, entitled “Vertical Farming Systems and Methods,” filed onNov. 30, 2018, which claims priority from US Provisional Application No.62/592,865, entitled “A Fully Automated Aeroponic Indoor Farming System,From Germination Through Harvest,” filed on Nov. 30, 2017, the entiretyof each which is incorporated by reference herein.

BRIEF DESCRIPTIONS OF THE DRAWINGS

FIG. 1 shows a growth structure according to an embodiment of thedisclosure.

FIG. 2 shows a growth structure column according to an embodiment of thedisclosure.

FIG. 3A shows a cavity according to an embodiment of the disclosure.

FIG. 3B shows a cavity fluidics system according to an embodiment of thedisclosure.

FIG. 4A shows a comb according to an embodiment of the disclosure.

FIG. 4B shows a growth module according to an embodiment of thedisclosure.

FIGS. 5A and 5B show a puck according to an embodiment of thedisclosure.

FIG. 6 shows a frog assembly according to an embodiment of thedisclosure.

FIG. 7 shows a tool assembly according to an embodiment of thedisclosure.

FIG. 8 shows an elevation mechanism according to an embodiment of thedisclosure.

FIG. 9 shows a module acquisition system according to an embodiment ofthe disclosure.

FIG. 10 shows a module acquisition system assembly according to anembodiment of the disclosure.

FIG. 11 shows a frog inner frame according to an embodiment of thedisclosure.

FIG. 12 shows a frog chassis according to an embodiment of thedisclosure.

FIG. 13 shows a frog function process according to an embodiment of thedisclosure.

FIG. 14 shows a set of frog components according to an embodiment of thedisclosure.

FIG. 15 shows an external controller according to an embodiment of thedisclosure.

FIG. 16 shows a control system according to an embodiment of thedisclosure.

FIG. 17 shows a rail structure according to an embodiment of thedisclosure.

FIG. 18 shows a rail structure junction according to an embodiment ofthe disclosure.

FIG. 19 shows a connector according to an embodiment of the disclosure.

FIG. 20 shows a frog and junction according to an embodiment of thedisclosure.

FIG. 21 shows an electrical configuration according to an embodiment ofthe disclosure.

FIG. 22 shows a light controller according to an embodiment of thedisclosure.

FIG. 23 shows a pre-pod fluidics system according to an embodiment ofthe disclosure.

FIG. 24 shows a pod fluidics system according to an embodiment of thedisclosure.

FIG. 25 shows a light column according to an embodiment of thedisclosure.

FIG. 26 shows an HVAC system with a growth structure according to anembodiment of the disclosure.

FIG. 27 shows an HVAC system with no growth structure according to anembodiment of the disclosure.

DETAILED DESCRIPTIONS OF SEVERAL EMBODIMENTS

Disclosed systems and methods may enable fully automated indoor farmingon a vertical plane. For example, some embodiments may automate theprocess of vertical farming from the moment the seed arrives to thefarming facility to the time the product exits the facility. Someembodiments may include mobile, multi-robot systems operating above agrowth structure to automate the growth, operation, repair, andconstruction of indoor farming facilities. Some embodiments may combineautomated robots, growth structures, growth modules, and/or softwarethat may optimize indoor farming processes.

In some embodiments, system hardware and/or software may automate thegrowth of one or more plants through applying and varying lighting,nutrients, and/or atmospheric compositions correspondent to the crop'sgenetics and/or stage of maturity, among other things. Robot systemsatop a growth structure may be responsible for, among many other things,the movement of plants (individually or as a group), the acquisition ofsensor data, the movement of lights and fluidics systems, and/orcleaning and maintenance subroutines that may be employed to operate anindoor farming facility without the interjection of human beingsthroughout the decision-making and execution process.

Some embodiments may completely automate the process of cultivatingbiological entities end-to-end, through seeding, germination,propagation, respacing, pollination, growth, harvest, cleaning,trimming, thinning, recycling, packaging, and/or storage, for example.Some embodiments may employ one or more combinations of, among otherthings, automated logistics, manufacturing, machine learning, artificialintelligence, mobile multi-robotics, and/or process-optimizationtechnologies that may not require human input for operation,maintenance, repair, improvement, and/or optimization of the system.Disclosed embodiments may accumulate information/knowledge pertaining toenvironmental characteristics and/or plant characteristics in order toproduce biological entities with optimal plant characteristics.Implementing a vertical-plane growing system may allow for increasedpacking efficiencies, improved airflow due to natural convection, and/ormore space efficient and/or energy efficient automation. Employingautomation mechanisms may decrease operational cost and/or may decreasethe pest and/or disease load experienced by the plants.

Embodiments may be configured to provide a variety of environmentalcharacteristics. Environmental characteristics may describe, in anon-limiting manner, one or more of the following attributes (some ofwhich are described in greater detail below): the electricalconductivity (EC) of the nutrient solution; the gaseous and aqueoustemperature; the airflow speed and direction in the root zone, foliarzone, enclosed environment, and/or external environment; air pressure;the gaseous and/or aqueous CO2 concentration; the gaseous and/or aqueousO2 concentration; the nutrient concentrations within the nutrientsolution; the water and nutrient flow; the pH of the nutrient solution;the oxidation reduction potential (ORP); the quality and intensity oflight within the growth arenas; the humidity of the root and foliarzones; the cleanliness of the air; the general state of the plants; thepest and disease state of the plants and/or system overall; and/or thelocation of equipment (e.g., pucks and/or combs, described in detailbelow) throughout the facility.

Embodiments may be configured to accommodate and/or encourage a varietyof plant characteristics. Plant characteristics of one or morebiological entities being farmed may describe, in a non-limiting manner,one or more of the following attributes (some of which are described ingreater detail below): mass of the biological entity; color [in visibleand nonvisible wavelengths] of the biological entity; sugar content ofthe biological entity, acidity of the biological entity, size of thebiological entity; shape of the biological entity; morphology of thebiological entity; growth rate of the biological entity; texture of thebiological entity; temperature of the biological entity; area of thebiological entity subject to illumination; area of the biological entitysubject to airflow; root area subject to irrigation; and/or theconsideration of one or more of these plant characteristics over time.

Embodiments may provide specific structural features that may facilitateplant growth. At its most basic level, a plant may be supported by agrowth medium and a surrounding support structure that secures thegrowth medium. Herein, the combination of these two components is calleda “growth puck.” The growth puck, with or without the growth medium andbiological entity, may be subject to movement through a “puck respacingmechanism.” Some components that the respacing mechanism may interfacewith may include, but are not limited to, the growth puck and a growthmodule (“comb”). The comb may be a component that can store many pucks,for example pucks stacked on top of one another, while allowing theplant housed by the growth puck to extend its roots and its foliage outof either side of the comb. A “sensor puck” may serve as a sensor suitethat may determine one or many environmental characteristics and/orplant characteristics within the controlled environment. A “spacingpuck” may increase the space between biological entities in the growthpucks. The generic term “pucks” may encompass the various types of puckslisted above and/or other puck variations.

The comb may be responsible for maintaining the collective orientationand structural rigidity of one or more growth pucks. The movement ofthese combs throughout the lifecycle of the plant, throughout thefacility, may be managed by one or more mobile robots called “frogs.” Afrog may move growth modules between the respacing mechanisms and thegrowth structures, for example. Frogs may communicate with each otherthrough a base communication station that may also relay a number oftask directives, for example managing the task sequences for the frogs.

Frogs may be configured to perform one or more “frog functions,” whichmay encompass the tasks that the frog is capable of performing. Thesetasks may include, but are not limited to, the following: comb or growthmodule movement within and outside of the growth arena; light re-spacingcloser-to and/or further-from the surface of the comb or growth module;light replacement/removal to/from the growth arena; cleaning,sterilization, and/or movement of the column's cavity structure,nozzles, and/or channel system; data collection of plant characteristicsand/or environmental characteristics and transmission of that and/orother data; trimming, thinning, pollination, nutrient delivery,illumination, maintenance, and/or manicuring of the biological entities;harvest, planting, and/or removal of biological entities; pest controland/or disease mitigation; audio delivery to the growth arena;atmospheric control; electromagnetic field manipulation; laser-basedmanipulation of the biological entity; communication networking;structural inspection within the growth arena; warehouse logisticsmanagement of things other than plants and biological entities;packaging harvested goods; storing growth modules, combs, and/or plantsfor certain periods of time; frog rescue [which may entail one frogpushing another frog around the facility in order to remove it frombeing in the way of other frogs and also delivering it to the frogelevator, recharge station, and/or a dead zone where frogs traditionallydo not operate]; and/or assembly, cleaning, maintenance, emergencyoperations, and/or servicing of the system.

In some embodiments, frogs may operate autonomously atop a matrix ofrails mounted to the top of a “growth structure,” which may supportrails on which the frogs move and/or support the pucks. The growthstructure may support many other subsystems in the controlledenvironments. The subsystems may include, but are not limited to, thefollowing: a “lighting system” that may be responsible for illuminatingthe biological entity; a “power distribution system” that may beresponsible for delivering power to lights, sensors, solenoids,actuators, and/or various other subsystems; columns that may providesupport, alignment, and/or housing of combs; a “fluidics system” thatmay be responsible for delivery of gaseous and/or aqueous solutions toplants' root zones; and/or, among other subsystems, rails for frogs totranslate across the top of the growth structure. Frogs may continuouslyreconfigure the array of combs housed in the columns of the growthstructure, as well as performing a number of other tasks within thefacility.

The growth structure may include a set of structural members that act assupport for the frogs' rails and the support of the growth cavitiescalled “columns.” Columns may include a vertically oriented set of railsthat may act as guides for the combs as they are lowered from the frog.Columns may provide a barrier structure that may isolate the roots ofthe plants from the foliar atmosphere and may contain the nutrient mixfrom escaping the internal cavity of the column. The internal cavity ofthe column may be enclosed by one or two horizontally opposed sets ofgrowth modules and side barriers that may be connected between therails.

Within a column's cavity, a fluidics system may be responsible fordelivery of the nutrient mixture to the back face of the comb whereroots may be are protruding from the back side of the respective growthpucks. The fluidics system may deliver the nutrient solution throughpipes, hoses, jets, nozzles, and/or various connection mechanisms.

Columns may include, on either side, one or more lights. For example,plants may grow towards a set of lights that are horizontally opposed.In some embodiments, the lights may include LED lighting componentsand/or other lighting components that may emit a specific quality andintensity of light that may be tailored to the crop in the combadjacent.

A system of ducts may be provided for regulating the temperature,humidity, CO2 concentration, O2 concentration, velocity, and/ordirection of the air between the lights and the plants. The ducts maydeliver conditioned air back the foliar atmosphere and/or may removeolder air from the enclosure.

A combination of computational hardware and software, referred to hereinas a “control system,” may perform control of the vertical farmingfacility. The control system may include a collection of hardware thatmay include, but is not limited to, the following: a sensor orcollection of sensors transducing the atmospheric composition of thefoliar atmosphere, root-zone atmosphere, growth arena atmosphere,Facility atmosphere and external atmosphere; a sensor or collection ofsensors transducing the state of the fluids being delivered to theplants on both the foliar and root side; a sensor or collection ofsensors transducing the state or some characteristic of the plant[including but not limited to size, morphology, color in multiplespectrums, etc.]; a sensor or collection of sensors transducing thestate of the system for the planning of logistics, sequencing, and/orother tasks for automated and manual execution; a piece or set ofhardware that interacts with the sensors to transmit, receive, store,manipulate, and/or visualize data; and/or a system of stationary andmobile digital imagery devices that capture, record and transmit imageryand/or video to determine a characteristic of the controlledenvironment, and/or characteristic of the plant, and/or a characteristicor state of the system.

On top of this hardware, the control system may include a software stackand/or one or more processors executing the software modules in thestack. The software stack may be responsible for the operation of theentire vertical farming facility. The control system may include one ormany of the following: a software module responsible for the regulationof the electrical conductivity (EC) of the nutrient solution; a softwaremodule responsible for the regulation of gaseous and aqueoustemperature; a software module responsible for the regulation of airflowin the root zone, foliar zone, enclosed environment, and/or externalenvironment; a software module responsible for the regulation of airpressure; a software module responsible for the regulation of gaseousand aqueous CO2; a software module responsible for the regulation ofgaseous and aqueous O2; a software module responsible for the regulationof nutrient concentrations within the nutrient solution; a softwaremodule responsible for the regulation of water and nutrient flow; asoftware module responsible for the regulation of pH; a software moduleresponsible for the regulation of oxidation reduction potential (ORP); asoftware module responsible for the regulation of the movement of pucksaround the facility; a software module responsible for the regulation ofthe movement of combs throughout the facility; a software moduleresponsible for the regulation of the quality and intensity of lightwithin the growth arenas; and/or one or more software modulesresponsible for one or more combinations thereof.

Embodiments may include sensors, which may be wired or wirelesslyconnected to computational hardware that may be responsible for thereceiving, storing, manipulation, and/or transmission of data. Sensorsmay be found in many locations within and outside of the controlledenvironment and/or mounted to various stationary and mobile devices orstructures such as, but not limited to, the following: sensor puckswithin the comb; sensors or sensor suites housed on the growthstructure; and/or sensors or sensor suites mounted to the frog and/orits subsystems. Sensor pucks may be responsible for sensingenvironmental characteristics and/or plant characteristics in the rootzone of the controlled environment and/or the foliar zone of thecontrolled environment. Sensors mounted to the growth structure may beresponsible for sensing environmental characteristics and/or plantcharacteristics in the root zone of the controlled environment and/orthe foliar zone of the controlled environment. Sensors mounted to thefrog may be responsible for the transduction of environmentalcharacteristics and/or plant characteristics within and/or outside ofthe controlled environment.

Stationary and/or mobile sensor and/or sensor suites may include, butare not limited to, the following: gaseous and/or aqueous temperaturesensors; gaseous and/or aqueous CO2 and O2 concentration sensors;aqueous pH sensors; ORP sensors; aqueous and/or gaseous flow sensors;aqueous and/or gaseous pressure sensors; gaseous humidity sensors;aqueous nutrient concentration sensors; aqueous electrical conductivitysensors; light quality sensors; light quantity sensors; digital imagingdevices; hall-effect sensors; optical sensors; scanners; light spectrumtransducers; and/or aqueous sensors involved in the transduction of atleast one of the following: nitrogen, phosphate, potassium, calcium,magnesium, copper, chlorine, boron, sulphur, zinc, molybdenum, iron, andmanganese.

Embodiments disclosed herein may transmit data among subsystems and/oroutside devices. Systems that may be involved in the transmission ofdata may include, but are not limited to, the following: a transmitterthat transmits data; a receiver that receives data; a transceiver thatboth sends and receives data; and/or a configuration of transmitter,receiver, or combination thereof (e.g., transceiver) that is eitherwired or wireless. The data, from a host of stationary and mobilesensors and sensor suites, may be used to determine and/or monitor theenvironment within which the plants are growing. This automatedmonitoring system, in conjunction with softwaremodules/algorithms/programs, may allow the system to adjust one or anumber of environmental characteristics through a number of differentactuation mechanisms in order to improve the plant characteristics ofthe biological entity.

For example, through consideration of the transduced environmentalcharacteristics and/or plant characteristics being accumulated throughthe sensors and the software modules that ingest, store, and/ormanipulate this data, the control system may be capable of makinginformed decisions regarding the controlled environment's operation andimplementing changes to the environment through various actuationmethods. Hardware and/or software that may be used to execute such tasksmay include, but is not limited to, one or more of the followingsoftware modules: a software module to accumulate and store data fromsome or all of the data accumulation devices within and outside of thecontrolled environment; a software module to analyze and manipulate thisincoming data; a software module and/or algorithm responsible foringesting the desired data and outputting determinations andrecommendations regarding the controlled environment and the actuatorsthat control the controlled environment to improve the characteristicsof the controlled environment; a software module to transmitrecommendations, wirelessly or by wire to another computational hardwaredevice that connects to the actuators that control the controlledenvironment; a software module that receives the instruction data and/orengages the actuators in a desired manner to improve the environmentalcharacteristics of the controlled environment, in order to improve theplant characteristics of the biological entities within the farm; and/orone or more software modules responsible for one or more combinationsthereof.

The process from environmental characteristic and plant characteristictransduction through actuation of various components to improve saidcharacteristics may include continuous reevaluation and modification ofthe controlled environment to ensure optimal environmentalcharacteristics, creating a closed-loop control system that manages theoperation of the farm. Locally, and/or in the cloud, a collection ofsoftware modules may be responsible for not only storing the data thatis accumulated, but also for the responses determined and implemented bythe control system and/or the effects of these decisions on theenvironmental characteristics and plant characteristics.

Some embodiments may leverage the combination of desired environmentalcharacteristics and plant characteristics and real-time and historicaldata flowing from the farm to learn using machine learning and/orartificial intelligence. A set of software modules and algorithms maytake in the data from the farm and compare it to historical data. If thesystem discovers a perceived improvement in the output plantcharacteristics, the system may update the environmental characteristicsimplemented in the next growth of the same crop. Using Internet ofthings (loT) and/or other sensor arrays and big data-sets, the systemmay begin to learn how to grow specific crops optimally in any facility.

To support the overall collection and management of data within thevertical wall indoor farm and to support the ability to extract andanalyze semantically meaningful data from that data and to represent andact on that information, some embodiments may include a cloud-basedsoftware architecture that may be remote from the physical site of thefarm. The data about plants and equipment in the indoor farm may be sentto the cloud through a data collection system that has been designed forindoor farms. The system may send the data to the cloud using thesensors and transmission hardware described herein. In the cloudenvironment, the data may be collected and organized into relationaland/or non-relational databases. An index that uses indoor farmingdomain information may be used to organize and access the data. Thecollected information may be transformed into a real-time assessment ofthe state of the various indoor farms. Much of this transformation maybe generated by machine learning algorithms that may detect patterns inthe data and detect anomalies and problems and/or interesting patternsof behavior. The state information may be used to continuously evaluatethe state of the system and schedule control actions for the farm, toimprove plant characteristics (such as changing nutrients, lighting, orenvironmental conditions), and/or the robots and automation. This closedloop control systems may reside in the cloud and/or may be maintainedlocally at the site of the farm for redundancy and security. A userinterface may be provided to enable farming domain experts and others tomonitor the information and control actions of the system.

The cloud-based information management system may be organized by anindoor-farming specific knowledge representation. This knowledgerepresentation may include a semantic representation of entitiesinvolved in the plant growth. The representations may be used to modelthe biological and physical environment within and outside of thefacility and may be be used by other software algorithms to monitorperformance, detect anomalies, and/or design and plan control actions,for example.

The representations may be organized into three major categories. Thefirst category may be information about plants. Each plant grown in theindoor farm may be uniquely represented through its life-cycle. This mayinclude continuously characterizing the state of the plant at each stagefrom germination to harvest. These characterizations may be obtainedfrom extracted sensor data information and may be probabilistic innature.

The second category may be recipes. Recipes may include representationsof knowledge about how plants should grow. This may include informationabout the various environmental characteristics to which the plant issubjected. It also may include models of the desired state of the plantat each stage in its life cycle. The recipes may include the desiredfinal nature of the plant (e.g., the plant characteristics). Thousands(or more) of recipes may be developed to represent different varietiesof plants and plants having different output plant characteristics. Therecipes may contain information about possible anomalies or diseasesthat might be associate with each specific plant.

The third category may be physical entities in the indoor farm. Thesemay include the physical environment, such as growth modules/combs,columns, pods, frogs, etc. These may also include the operatingsubsystems, such as fluidics, lighting, HVAC, sensors, and othersubsystems. For each physical entity, the expected characteristics andoperating modes may be represented along with the state of the subsystemat various times.

Some embodiments may include systems configured to diagnose a state ofand/or anomalies with plants growing within the indoor farm. This plantenvironment diagnostic software system may reside in the cloud in someembodiments. The plant environment diagnostic software system may usethe knowledge representations to compare actual plant status andbehavior (per the data collected from sensors and extracted into theknowledge representations) with the expected behavior represented in therecipes. This diagnostic system may evaluate the state of each plant andmay provide a probabilistic rating of how well the plant's state matchesthe recipes. The diagnostic system may detect possible pests, diseases,or other anomalies that may be present in the plant. This may be done bycomparing the plant information in the recipes with informationcollected and represented about the plant, for example. The system maywork independently on each plant in the indoor farm.

Detection methods used by some embodiments may be based on a Bayesianmodel. For example, the system may develop a set of hypotheses from therecipes about the expected state of the plants. There may be hypothesesabout the presence of pests or diseases in the plant. The algorithm maycompute the probability of a hypothesis being true given theevidence—P(H|E)—the probability of the hypothesis (H) being true isconditional on the evidence (E) collected. This may be accomplished bycomputing the probability of observing E given H—the likelihood thatsuch evidence would exist given the hypothesis. This may be multipliedby the likelihood of each hypothesis existing, which may result in alist of probabilities for each hypothesis.

As more data is collected and as recipes are developed, the softwaresystem may be able to “learn” new information about recipes and aboutthe hypotheses about the observed state and behavior. This recipelearning system may compare each hypothesis developed with a groundtruth model that may indicate how well the system performed in assessingthe probability of that hypothesis. Ground truth data may be obtained byobserving the actual outcome of various plants using both automated andmanual training methods. The system may automatically adjust the priorprobability of a hypothesis. This may enable the system to improve itsmethods of confirming or refuting hypotheses. The system may also detectpatterns of behavior and plant growth outcome that may suggestalternative ways to grow the plants.

The software architecture, knowledge representations, and/or diagnosticand analysis tools may be applied to multi-farm data collection andmanagement. The system may be centralized in one or more cloudlocations, but may have access to the growth and performance data ofinformation collected world-wide. The system may uniquely analyze andcompare data from many locations and plant types to better accomplishits analysis and recipe Learning.

FIG. 1 shows a growth structure 101 according to an embodiment of thedisclosure. Considering one or many growth structures 101 within afacility, a plurality of structures called pods may be built adjacent toone another and each may include one or more columns as described inFIG. 1 . Growth structure 101 may be an enclosed environment wrapped ina specifically thermal- and light-resistant material to isolate thestructure from the environmental conditions outside of the growthstructure 101. The pods may be characterized by the volume andcomponents between a pair of uprights 103 and 104 of various andconfigurable heights (18 foot and 24 foot uprights, respectively, inthis example) that may be connected by a number of load beams 102 atvarious heights along their vertical axis of the upright. The pods maybe used for the structural support of the columns in FIG. 2 , thoughthey may have the capacity to house different subsystems likefertigation, power distribution, power storage, growth module transferarea, etc. These columns in FIG. 2 may be responsible for thepositioning and housing of combs (e.g., see FIG. 4A) or growth modules(e.g., see FIG. 4B). These growth modules/combs may be populated byvarious configurations of biological entities (e.g., see FIG. 3A) thatmay be subject to optimal and varying lighting, nutrient, andatmospheric conditions called environmental characteristics. Growthmodules/combs may be relocated by one or more frogs (e.g., see FIG. 7 )which may translate and actuate atop a system of rails (e.g., see FIG.17 ). In addition to being used for growth, structures 101 may be usedfor pre-processing, post-processing, storage, control, viewing,maintenance, and/or hardware. These areas may be configured andconstructed in such a way that they are incorporated into a form factorthat is compliant with the warehouse and the pallet racking structuresbeing used to house the facility.

FIG. 2 shows a cavity or column 200 according to an embodiment of thedisclosure. The growth structure 101 may include a collection of podssupported by uprights 103/104 and load beams 102. The growth structure101 may include pallet support beams (e.g., see FIG. 3A), row spacers(which may define the lateral distance between uprights 103/104), andbolts securing the feet of the uprights 103/104 to the surface uponwhich the growth structure 101 stands. Pods may be populated with aplurality of cavities or columns 200. Detachably attached to the growthstructure 101 may be a set of channels (e.g., see FIG. 3A), fluidicsLines (e.g., see FIG. 3A), light columns 201, nozzles (e.g., see FIG.3A), drainage trays (e.g., see FIG. 3B), HVAC ducting, and sensors thatcollectively may comprise a column 200. A plurality of these columns 200may be arranged adjacent to one another, in variable spacings, toconstitute a pod. A plurality of these pods reside in a volume known asthe growth arena 101. One or many of these growth structures 101 may becombined to create a facility.

FIG. 3A shows a detailed view of cavity or column 200, in which top ofthe cavity is highlighted in FIG. 3A and the bottom of the cavity ishighlighted in FIG. 3B according to an embodiment of the disclosure.Cavity 300 may be made up of various components that may mount to thegrowth structure 101 and may contain the nutrient solution beingdelivered by the fluidics. A light column 2500 may hang from palletsupport beams mounted on the growth structure 100. A light column mayinclude a pallet support beam 301 and a plurality of LED lights 308 and322 that may be suspended by vertically oriented straps 307. The cavity300 may have a pair of cavity channels 304 that may be connected to eachother via a piece of corrugated plastic 302 or other material, calledthe corrugated plastic barrier, that may be mirrored between two loadbeams. The combination of cavity channels 304 and the corrugated plasticbarrier 302 form a grouping called a skirt. There may be a skirt on bothsides of the cavity 300 facing inwards toward the cavity fluidicssystem, which may include nozzle 309 and fluidics lines 312. Cavitychannels 304 and 321 may be mounted by skirt mounts 305 to a load beamat various heights to ensure rigidity and position maintenance. Thesecavity channels 304 may be responsible for guiding the growthmodule/comb 313, and the biological entities 310 supported by it, intoand out of the frog to its desired position in the growth structure,then keeping it secure from falling or contortion whilst also ensuringthat no nutrient solution escapes from the column's cavity. The palletsupport beam 306 may mount to the load beams at either end by palletsupport mount 303 and may provide support for the cavity fluidicssystem. The cavity fluidics system may be supported by the palletsupport beam 306 through a set of cavity fluidics support hooks 311,which may allow for simple insertion and removal of the cavity fluidicssystem.

FIG. 3B shows a cavity fluidics system according to an embodiment of thedisclosure. The cavity fluidics system may include various componentsthat deliver a nutrient mixture to the roots protruding out of thegrowth modules/combs situated in the column. The nutrient mixture mayenter through a bulkhead gasket through the bottom of the drainage tray324 that is being supported by pallet support beam(s) 323 at the bottomof the cavity. The nutrient mixture may travel through a fluidics line312 (e.g., a PVC pipe) to be split into a varying number of nutrientdelivery lines. The configuration of the nutrient delivery lines may bebased upon the desired nutrient distribution pattern and dimensionswithin the column's cavity. Nutrient solution that does not get absorbedby the biological entity may flow downward to be collected in thedrainage tray 324, then further distributed from a drainage bulkheadgasket back to the more centralized fluidics system that the nutrientsolution came from.

FIG. 4A shows a comb 400 according to an embodiment of the disclosure.The comb 400 may be configured to organize and secure a group of pucks,such as growth puck 401. The comb 400 may be a collection of many growthpucks 401, “sensor pucks,” and “spacer pucks” in any number of layersand configurations. The comb 400, in this incarnation, may include ahorizontal member 402 made from formed sheet metal with fasteners (e.g.,PEM fasteners) placed at intervals along the member. These PEM fastenersmay align with the growth puck alignment hole (e.g., see FIG. 5 b ) onthe top of the growth puck 401 so that the puck's first layer is in aknown configuration to dictate the placement of more pucks on top ofthat first layer. In this example, the dimensions of the comb 400 are 40inches wide and 24 inches tall, though the height and width may bevariable. Combs 400 may be picked up by the bottom member through aslightly varied module acquisition payload as outlined in this document.Any number, combinations, and configurations of growth pucks 401, sensorpucks, and spacer pucks may be provided.

FIG. 4B shows a growth module 411 according to an embodiment of thedisclosure. In some embodiments, growth module 411 may be anoff-the-shelf, 4 foot by 2 foot component. Growth module 411 may be madeout of polystyrene foam or another material with growth module holes 412formed therein. The holes 412 may be bored out in various configurations[staggered, square; 18 holes, 36 holes, 72 holes, etc.] to accommodatedifferent crops with different static and dynamic spacing needs. Thesenon-dynamic plant-spacings may be used in place of the comb 400 with itsdynamic plant spacing capabilities in some cases. The combs 400 andgrowth modules 410 may be a similar form factor such that they may bothbe interchangeable platforms for growth of the biological entity insideand outside of the growth arena.

FIGS. 5A and 5B show a puck 500 according to an embodiment of thedisclosure, where FIG. 5A shows the puck 500 from a top side, and FIG.5B shows the puck from an underside. For example, puck 500 may be agrowth puck, which may be the component responsible for housing,supporting, and orienting the biological entity 505. Puck 500 may havean opening 504 where the growth medium 506 and biological entity 505 maybe slid in at one or various times throughout the lifetime of thebiological entity 505, for example at the beginning of the biologicalentity's lifecycle. Puck 500 may allow for the biological entity 505 tobe moved around individually without causing harm to any portion of thebiological entity. Pucks 500 may be configured to interlock with eachother in two or three dimensions such that they can be arranged in anarray and thereby form a comb.

When the growth puck 500 is placed onto the comb's 400 horizontal member402, the growth puck opening 504 may align with features along thehorizontal member 402 that may be configured to properly space thegrowth pucks 500. The female alignment channel 501 and the malealignment channel 503 may be used to interlock the growth pucks 500together. When a growth puck 500 is lowered down onto another growthpuck 500, the growth puck nub 502 of the growth puck 500 below mayengage the growth puck alignment hole 507 on the growth puck 500 beinglowered. In conjunction with the male 503 and female 501 channels, thegrowth puck 500 may be secured in-place within the comb 400 using thesealignment and securing mechanisms. There may or may not be a gradient508 on the top and/or bottom surfaces of the puck 500 to ensure that anystray liquid may flow back into the cavity rather than out toward thefoliar zone.

A growth puck 500 may include the growth medium or have the capacity tosecurely house a separate growth medium. Pucks 500 may be made of anumber of materials, including but not limited to, the following:polyethylene, ABS, polypropylene, polystyrene, polyvinyl chloride, etc.Pucks 500 may be be negatively and/or positively buoyant. Pucks 500 maybe a variety of colors. In some embodiments, colors may be chosen toprovide contrast against the plant matter. Each individual growth puck500 may be tracked using the farm's operating system to make sure thatthe data associated with the plant being observed is stored withreference to the correct biological entity/growth puck 500.

The growth puck 500 may be configured to interface with a puck respacingmechanism that may relocate growth pucks within combs to correspond tothe requirements of the plant. This interface between the growth puck500 and the puck respacing mechanism may include a variety of differentmechanisms, including but not limited to, the following: friction,magnetic, suction, etc. The pucks 500 may combine together within thecomb's 400 matrix to limit or prevent the escape of fluid from the rootcavity and/or to limit or prevent light from entering the root cavity.Pucks 500 may be any number of different shapes and sizes. Pucks 500 maybe made of multiple components or a single component.

Some pucks 500 may be spacer pucks, which may also interface with thecomb 400 and the puck respacing mechanism. The spacer puck may be usedto increase the distance between growth pucks to mitigate leafovershadowing and therefore optimize plant spacing. Spacer pucks may bemade of the same material(s) as the growth puck and may potentially bethe same shape and/or dimensions as the growth puck, though in someembodiments they may be of different size and/or construction. Spacerpucks may be the same dimensions as the growth puck, though notnecessarily. Spacer pucks may use the same securing mechanisms (male andfemale channels, nub and hole) as growth pucks to interlock into thecomb's array seamlessly. The spacer puck may be a passive entity thatmay provide optimal spacing between growth pucks and sensor pucks andthat may ensure no light enters the root-zone cavity and no nutrientspray escapes the root-zone cavity. Spacer pucks may also serve as atruth reference for the vision processing system in terms ofreflectivity, dimensions, locations, angles, position, and other truthdata, as described below.

Some pucks 500 may be sensor pucks, which may also interface with thecomb 400 and the puck respacing mechanism. The sensor puck may providedata descriptive of the boundary layer of air beneath the canopy of theplants and also data descriptive of the root-zone environment. Enabledby improving battery technology and distributed wireless sensorsnetworks (IoT), the sensor puck may be placed strategically within thecomb 400 to allow for optimal spacing of growth pucks. The sensor puckmay deliver data wirelessly back to a more centralized computer in someembodiments. Sensor pucks may be made of the same material(s) as thegrowth puck and may potentially be the same shape and/or dimensions asthe growth puck, though in some embodiments they may be of differentsize and/or construction. Sensor pucks may be the same dimensions as thegrowth puck, though not necessarily. Sensor pucks may use the samesecuring mechanisms (male and female channels, nub and hole) as growthpucks to interlock into the comb's array seamlessly. Sensors within thesensor puck may transduce environmental characteristics such as temp,air flow, humidity, light intensity, and light quality among otherthings, and even plant characteristics as well in some embodiments. Whenthe comb 400 is brought to the plant respacing mechanism, as describedbelow, these sensor pucks may remain in the comb or may be removed formaintenance, recharging, cleaning, or replacement.

The “puck respacing mechanism” may be the mechanism that is responsiblefor the pucks 500. The puck respacing mechanism functions may include,but are not limited to, the following: acquisition/placement of pucks[growth pucks, spacer pucks, sensor pucks] into and out of the comb;placement and acquisition of pucks onto and from transport mechanisms[e.g. conveyor lines] delivering and removing pucks to/from the puckrespacing mechanism; and/or positioning of pucks directly into othersubsystems [e.g. cleaning, image capture, puck rotation, etc.].

FIG. 6 shows a frog 600 assembly according to an embodiment of thedisclosure. The frog 600 may be an automated wheeled robot that may bedesigned for singular or multi robot implementations. The frog 600 maybe responsible for the automation of tasks and subsystems within thefacility. The term “frog” may refer to any variation of the frog 600that is responsible for any of the frog's functions outlined herein. Insome embodiments, different frogs 600 may vary in hardware, dimensions,software, and any other characteristic or capability laid out withinthis document.

The frog 600 may include an outer frame 601 and an inner frame 607 thatmay be raised and lowered to change the direction of travel using alinear actuator 602. Inner and outer frame guides 609 may maintainalignment between the outer frame 601 and inner frame 607. Somecombination of passive wheels 610 and/or active wheels 611 may give thefrog 600 the ability to actuate along rail mechanisms. Within the innerframe 607 there may be some combination of one or many elevationmechanisms 603 and/or payload bars 606. In this incarnation, theelevation mechanism 603 may be connected to the module acquisitionsystem 606 by a set of retractable straps 604. The frog's channels 608may work in conjunction with the elevation mechanism 603 and moduleacquisitions system 606 to guide the growth module/comb into and out ofthe frog 600. There may also be a set of computational hardware in thefrog's brain 605 that may control activities of the frog 600.

In some embodiments, the frog 600 may be a battery powered,multi-wheeled robot that may have the capacity to locate itself within afacility, communicate to and from a ground controller and/or other frogs600, operate autonomously based on directives received by those othersubsystems, and/or and automatically return for maintenance, recharging,hard-wire data transfer, recalibration, or downtime in a designated areain the growth arena.

In some embodiments, the coarse positioning of the robot may be knownand controlled through an ultra-wide band system of anchors and tagsthat may be used to locate the frog 600 in three-dimensional space. Theanchors may be placed in various locations throughout the facility, andthe tags may be located on each individual frog 600 (e.g., on a topsurface). The ultra-wide band system may provide information to the frog600 describing exactly where it is and over which junction it resideswith an accuracy of ±10cm in some embodiments.

In order for the frog 600 to achieve position control of ±2.5mm accuracyin some embodiments, a fine-positioning control system called thejunction alignment sensor may be provided on the frog 600. The frog 600may use a number of mechanisms for fine position control; described hereare three of those many potential options described as junctionalignment sensors.

A first position control option may use hall-effect sensors and magnets.At the corners of each junction within a facility, there may be 4-wayPVC connectors (e.g., see FIG. 20 below) that may house a magnet in adefined location. The frog 600 may include a hall-effect sensor that maysense the magnetic field flux as the frog 600 arrives at the junction. Amicroprocessor on-board the frog 600 may detect the peak magnetic fieldflux and may detect how many encoder counts past the peak magnetic fieldflux the frog 600 traveled as it slows. The frog 600 may reverse theexact number of encoder counts to align itself properly with the magnet.

A second position control option may employ a system of distance sensorsto determine a frog's 600 position above the junction. Two groups of twodistance sensors may be attached to the bottom of the inner and outerframe of the frog 600. These distance sensors may be oriented such thattheir beam is sent downwards at a 45° angle toward the central long axisof the rail, for example a PVC pipe. As the frog 600 arrives at ajunction, the pair of distance sensors that are positioned to detect therail with the long axis parallel to the direction of travel may remainpassive. The pair of distance sensors that are oriented to detect therail perpendicular to the direction of travel may be engaged. As therail is detected by the distance sensors, the distance sensors may lookto achieve an identical distance from each distance sensor. This maysignify that the frog 600 may be positioned directly above a junction,therefore it can actuate in either direction or engage the components(e.g., growth modules) beneath it at that junction.

Another position control option may include a vision system. As the frog600 translates atop the growth structure, a set of cameras on the frog600 may fixated on the rail system. Variations in the rail system maysignify various things to the frog 600. For example, a camera at thecorner of the frog 600 gazing straight down at the pipe may provideinformation allowing the frog's 600 processor to able to determine thelocation of the 4-way PVC connector using various vision processingalgorithms. In some embodiments, the frog's 600 brain (e.g., amicroprocessor) may expect a certain feature in the image to berepresented by specific colors and light intensities on certain parts ofthe camera's sensor. At the moment the camera identifies, isolates, anddynamically tracks those features, the frog 600 may translate to aposition where those features are appearing in the correct location onthe camera's sensor, signifying correct positioning of the frog 600above a junction.

In all of these fine positioning scenarios, a microprocessor in thefrog's brain 605 may execute a closed feedback to find the predeterminedoptimal location. When that location is found within some tolerance, thefrog 600 may set all 8 of its wheels onto the rail to ensure that thepositioning of the frog 600 is correct. The frog 600 may use the railsystem as a reliable reference for correct positioning of the frog 600by dropping all 8 wheels onto the junction.

The frog's brain 605 may be responsible for the decision making andexecution of the frog's directives to the actuators on board, and thecommunication of information to systems outside of the frog 600. Thefrog's software flowchart (see FIG. 14 below) outlines an exampleiteration of the frog's software loop. As described below, the softwaremay consider communications with ground controller, emergency handling,task scheduling, and task fulfillment, for example.

FIG. 7 shows a tool 700 assembly according to an embodiment of thedisclosure. The tool 700 may include an elevation mechanism 701 andpayload bar 702. Considering the array of frog's functions, the tool 700may provide either an interchangeable subassembly that the frog 600 mayactively swap in and swap out, or the tool 700 may be a fixedsubassembly that is not interchanged. The elevation mechanism 701 may beconnected to the payload bar 702. This tool combination may be used forgrowth module and/or comb acquisition and deposition. Various toolcombinations may be used to complete the other frog 600 functions withinthe facility.

FIG. 8 shows an elevation mechanism 800 according to an embodiment ofthe disclosure. The elevation mechanism 800 may include a rotating bar803 that may be mounted to the frog's internal chassis with a dc motor802 and encoder 801 at either end of the assembly. Belts 809 reachingdown to the payload bar may be spooled into two rolls 804 which may bewound around the axis of the rotating bar 803. The belts may extend downto the payload bar 702 along with a power and communication ribbon thatmay be spooled on the wire spool 806. The slip ring 807 may allow thebar to rotate and the wire to spool without impinging or affecting thewire connecting to the frog's brain 605. The elevation mechanism 800 mayreceive commands from the frog's brain 605 pertaining to the desiredvelocity and elevation of the payload bar 702 through actuation andcontrol of the dc motor 802 and encoder 801, for example. The elevationmechanism 800 may perform elevation maneuvers to raise and lower thepayload bar 702 under various position and velocity control algorithms.Many of the frog's functions may employ this elevation mechanism 800 andits ability to perform elevation maneuvers. The elevation mechanism 800and payload bar 702 have limit switches mounted in order to sense whenthe payload bar 702 has come into contact with another surface. Theelevation mechanism 800 may include a ratchet gear and pawl subsystem808 to ensure the elevation mechanism 800 does not change its state inthe event of a subsystem failure. Along the elevation mechanism theremay be couplers 805 that may connect various components.

FIG. 9 shows a module acquisition system 900 according to an embodimentof the disclosure. The payload bar 702 may be a hardware platform thatmany different subsystems may be mounted to in order to be lowered totheir desired 3D positions within the facility. The example used in thisinstance is the module acquisition system 900. Other examples mayinclude, but are not limited to, the following: light acquisitionsystem, cavity cleaning system, sensor suite payload, etc. Variousiterations of the payload bar 702 may include the belts from theelevation mechanism 902 and 903] and the payload bar platform 907.

In the module acquisition system 900, a group of components maycollaborate to pick up, lift, lower, and release growth modules orcombs. The runner 901 may be mounted to the payload bar platform byrunner mount 904. Hooks 906 may be connected to the payload bar toensure a reliable connection between the elevation mechanism and thepayload bar. The module claw may be made up of the payload bar mount905, the gripping servo 908, and the module clamps 909. The grippingservo 908 may be responsible for actuating the module clamps 909 so thatthe distance between the module clamps 909 decreases when making agrowth module/comb connection, maintains grip duringmovement/relocation, then releases after the movement has beencompleted. One or more of these module claws 909 may be actuated to makea reliable connection to the growth module/comb.

To perform other frog 600 functions, portions of the payload bar may bereplaced, and other components added. In the case of the sensor suitepayload, the module claws may be removed. In the place of the moduleclaws, other items may be installed. For example, a potentialcombination of the following hardware may be installed: multispectral,hyperspectral, mono-spectral, and/or IR cameras of various hardwarecapabilities, CO2 sensors, O2 sensors, humidity sensors, airflowsensors, inertial measurement unit (IMU) temp sensors, barometricsensors turbidity sensors, movement sensors, light sensors, distancesensors, lidar, power lasers, and processing, storage and communicationhardware that can process, store and communicate the accumulated data toanother location.

FIG. 10 shows a module acquisition system assembly 1000 according to anembodiment of the disclosure. Two elevation mechanisms 1001 and 1002 andtwo corresponding module acquisition system payloads may be situated aspecific distance from one another considering the requirements of thebiological entity and the growth module/comb housing the biologicalentity. Two sets of frog channels 1004 may be used to align the cavity'schannel in the growth structure beneath the junction that the frog 600is positioned above. The frog's channels may help to guide the growthmodule/comb in and out of the frog 600 and growth structure to ensureseamless acquisition and deposition of growth modules/combs.Additionally, the module acquisition system runner 901 and 1003 may beused to ensure the growth module/comb does not become disoriented whileit is being acquired, stored, relocated, or deposited. The frog'schannels may help to keep the growth module/comb properly orientedduring the frog's movements around the facility.

FIG. 11 shows a frog inner frame 1100 according to an embodiment of thedisclosure. The frog's inner frame 1100 may house the elevationmechanisms 1102, the module acquisition system payload 1103, frog'schannels 1004, the frog's direction change actuator 1101, and the frog'sinner and outer frame guides 1104. The frog's direction change actuatorin this instance may be a linear actuator the presses the outer frame's[see FIG. 12 ] wheels off the ground when extending and lifts the innerframe's [see FIG. 12 ] wheels off the ground when retracting. Othermethods of direction change may be possible using gears, transmissions,belts, chains, and/or a number of other techniques. The frog's inner andouter frame guides may ensure that the inner and outer frames remainproperly spaced.

The frog's inner frame 1100 may support multiple elevation mechanisms invarious locations to perform various functions. Due to the dimensions ofthe inner frame and junction configuration, the elevator mechanism maylower a payload bar into any portion of the growth arena [e.g., bothcavities on either side, between lights and plants on either side, andbetween two light columns].

Various sensor suites sensing the state of the component being actuatedon [plants, lights, etc.] and sensing the state of the frog 600 itselfmay be disposed inside the volume of the frog's inner frame 1100.Various frog configurations may have varying dimensions and junctionspans. Some frogs 600 may span one junction, and/or some frogs 600 mayspan many junctions depending on which frog function they are assignedto perform.

FIG. 12 shows a frog chassis 1200 according to an embodiment of thedisclosure. The outer frame of the frog 1201 may serve a number offunctions for the frog 600, such as, but not limited to, the following:mounting of frog's brain 605, of the frog's direction change actuator1101, the frog's outer-frame movement system1203, protective andstylistic covering of the internal contents of the frog 600, ultra-wideband tags for coarse positioning, indicator lights and screens,antennae, speakers, general lights, maintenance bays, connection pointsfor easy movement into and out of the growth arena, and sensors todetect various environmental characteristics and plant characteristics.

The frog's outer frame 1201 may be responsible for mounting the frog'souter-frame movement system 1203 for one direction along the rails. Inthis instance there may be a set of four wheels 1203 mounted such thatthey align with the rails on the top of the growth structure. At leasttwo of these wheels may be actuated using dc motors and encoders, withthe remaining number of the wheels being passive.

The frog's inner frame 1100 may be responsible for mounting the frog'sinner-frame movement system1204 for one direction along the rails. Inthis instance there may be a set of four wheels 1204 mounted such thatthey align with the rails on the top of the growth structure. At leasttwo of these wheels may be actuated using dc motors and encoders, withthe remaining number of the wheels being passive.

In this example the frog 600 may be mounted atop the growth structurewith concave wheels engaging a system of convex pipe rails. In othermanifestations the wheels may be convex and the rails concave inprofile; the frog 600 may be suspended from a structure connected to theroof; the frog 600 may be mounted atop a substructure that connects tothe roof or the growth structure. In any case, this disclosure mayinclude any single-robot or multi-robot system that operates above thegrowth of a biological entity in a vertical farm. A single frog 600 maybe responsible for all of the subsequent tasks listed hereunder.However, in many circumstances, a group of frogs with varying hardwaremay perform separate tasks within the farm.

FIG. 13 shows a frog function process 1300 according to an embodiment ofthe disclosure. Process 1300 may be an iteration of the frog'shigh-level software loop. At the beginning of the iteration, the frogmay check for packets 1301 coming from ground controller containinginstructions or general information. After the packet has been processed1302 and the frog's state updated 1303, the frog may enter a loop toascertain whether all of the failure checks on-board the frog have beenpassed.

The loop may include acquiring a current frog status 1304, determiningwhether an unrecoverable failure state exists 1305 and, if so, haltingthe processing 1306. If no failure exists and/or if all failure statesare resolved 1307, the frog may issue a system all clear 1308.

Once a frog is cleared for its next task, the task may be assigned. Ascheduling algorithm may determine whether there are unassigned tasks1309 and, if so, may identify any idle frogs 1310. The task may beassigned to the frog 600 with the hardware capacity and availability toexecute the task in question. For example, processing paths foridentified idle frogs 600 may be computed 1311, and the available frogwith the lowest-cost path may be assigned to complete the task 1312, atwhich point that frog may generate a sequence of commands to executeusing the various actuators on-board. The system may be updated 1313.

At this point, the frog 600 may go into a loop that constantly monitorsthe performance of the task execution against the expected timing andsequencing required for that specific movement. For example, frog brain605 may acquire the current frog state 1314 and determine whether acommand is active 1316. If not, the frog 600 may be reported as idle andmay receive a next command 1316. If the frog 600 has a current commandactive, a command state may be polled 1317 and evaluated to determinewhether it matches a checklist 1318. If so, the frog brain 605 maydetermine whether the command is finished 1319 and, if so, may loop backto 1315. If the command is not finished, frog 600 may be evaluated todetermine whether response and timing are expected 1320 and, if so, maybe reported as idle. If checks fail at 1317 or 1320, a failure may bereported and frog brain 605 may monitor for a halt command 1321.

Upon completion of the task at hand, the frog 600 may check forsubsequent commands from ground controller or the network of frogs 600on duty. This loop may be versatile and fault-tolerant and may allow thefrog 600 to receive emergency directives from ground controller or otherfrogs 600 as an emergency interrupt in-case of a system failure.

The following is a non-exhaustive list of examples pertaining to thetask scheduling loop in the iteration. These examples give a feel of thetask scheduling and execution that occurs on the frog 600 during itsoperation. Included in these examples are a light movement/acquisitionsequence, data acquisition/sensor deployment sequence, columncleaning/sanitization sequence, recharge/data-upload sequence, and afacility construction sequence. All are high level examples thatexemplify the versatility of the frog 600 in the vertical farmingsetting.

The light movement/replacement sequence may proceed as follows. Withinthe growth arena, adjacent to the growth modules/combs situated in thecolumn, a light column 301 may hang from pallet support beams mounted onthe growth structure as noted above. A support-frame suspended from theload beam may drape one or more belts/cabes/fibers/straps downward tothe bottom of the column as noted above. The lights may be connected tothe straps to orient the lights in such a way that efficiently,sufficiently, and optimally illuminates the biological entity. It may beuseful to actively vary the distance of the lights from the plants sincethe ratio of light emission to plant absorption may improve as thelights get closer, assuming the LED lights are distributed enough tomaintain ample coverage over the canopy.

The frog 600 may localize itself on top of a junction that sits abovethe desired light column. The frog 600, utilizing a similar mechanism tothe elevation mechanism [though they could potentially be the samemechanism] called the light acquisition mechanism, may reach down to theconnection point on the light column. The frog 600 may lift the lightcolumn up from its seat on the load beam. In the case where the frog 600is adjusting the light-to-plant distance, the frog 600 may translatesuch that the lights either move farther away or closer to the growthmodules/combs. Once the frog 600 has performed its plant-relocationdirective, the frog 600 may lower the light column's frame back onto theseat of the load beam and may query ground controller for a newdirective using process 1300.

In the case of light acquisition, the frog 600 may reach down to theconnection point on the light column and may pick the frame supportingthe light column up and away from the load beams. The light acquisitionsystem may begin to spool up the light column into a roll; otherstacking or folding mechanisms may be implemented to achieve the samegoal. Blind-mate connectors up the top or bottom of the growth structuremay allow the light columns to be actively removed and replaced withoutmanual disconnect.

The data acquisition and sensor deployment sequence may proceed asfollows. A variant of the frog 600 may have the capacity to house anddeploy the sensor suite payload. Portions of the sensor suite may beattached to the chassis of the frog 600, but many of the sensors may bemounted to the sensor suite payload. This sensor suite payload, with asimilar or identical elevation mechanism that the module acquisitionsystem payload employs, may have the capability of transducing any andall plant characteristics, environmental characteristics, and variousother states of the system. The data may be sent back to the frog'sbrain 605 for both storage and transmission to other electronic hardwarewithin and eventually outside of the facility, according to process 1300with data acquisition as the frog task.

The column cleaning, sanitization, and testing sequence may proceed asfollows. The frog 600 may have the capability to clean the interior ofthe cavity of the column. To clean the column, a varying collection ofUV lights, bristles, sprays, sensors, and swabs (the “cavity cleaningsystem”) may attach to the payload bar. In this circumstance, the combssitting in the column may be removed for relocation before the cleaningcycle is begun. Once emptied, the cavity cleaning bar may be lowereddown using the elevation mechanism. Throughout this process the UVlights, oriented in such a way that every surface of the column isilluminated by the UV light, may blast the column to kill unwantedbiological matter. The cavity cleaning system may brush, spray, and swabany portion of the column as part of a collection of components thatclean and sanitize the surfaces and orifices within the column,including the rails that guide the combs. The sensors on the cavitycleaning system may accumulate data on plant characteristics andenvironmental characteristics to transduce the state of the column'sstructures and surfaces. These functions may be provided as frog task(s)under process 1300. At the end of the cleaning process, the cavitycleaning system may deliver the data back to the frog's brain 605 forfurther transmission to other electronic hardware within and/or outsideof the facility. Physical data (for example the swabs from the cavity)may be deposited in a location that may be accessed by humans and/orautomated machines.

The recharge and data upload station sequence may proceed as follows. Arecharge station may be situated on the periphery of the frog's tracksystem. There may be one or many recharge stations depending on the sizeof the facility, number of frogs, variety of frogs, etc. The rechargestation may provide a place where the frog 600 can auto-recharge andform a hard-wire connection to a data upload link. In this instance, thefrog 600 may translate over to the recharge station under the command ofground controller or the frog's brain 605 and according to process 1300for in a variety of circumstances, including, but not limited to, thefollowing: low-battery, data-storage is full, all tasks are complete,etc. In this instance the frog 600 may align itself with the rechargemechanism that may use induction charging or some other method torecharge the batteries on-board the frog 600. The hard-wire data uploadlink may include a set of connectors and contacts that may allow thefrog 600 to communicate large amounts of data at a high transfer rate.

A variety of information may be transmitted, including but not limitedto the following: historical telemetry data, sensor data, health status,etc.

The facility construction sequence may proceed as follows. In somecases, the frog 600 may be responsible for theconstruction/deconstruction of the facility before, during, and/or afteroperation. The structures of the farm may be designed such that the frog600 may be responsible for the construction and deconstruction ofcertain elements of the facility. For example, after the growthstructure is constructed (e.g., the structural members that support thecavities, wrapping, lights, fluidics, etc.; and the rails that the frogtranslates upon in addition to other subsystems), the frog 600 mayinstall, construct, and/or deconstruct the following subsystems: lightcolumns, columns, fluidics subsystems, HVAC subsystems, etc. Forexample, the construction and deconstruction of the column may pertainto the placement and removal of sections/components of the column'scavity and comb guide-rails 302 and 304. The installation and removal ofthe fluidics subsystems may pertain to the piping, hosing, junctions,connectors, and nozzles that may be responsible for receiving the fluidand delivering it to the roots within the column's cavity. The frog'sresponsibility to install, relocate and remove HVAC subsystems from thegrowth arena may include the frog 600 connecting to various HVAChardware [ducting, junctions, baffles, VAV boxes, supports, etc.] andspooling, folding, stacking the subcomponents such that they can beconfined within the internal volume of the frog, etc.

FIG. 14 shows a block diagram of frog components according to anembodiment of the disclosure. This diagram outlines major subsystems,their components, and the communication channels between them. Theglobal localization system 1402 may be the coarse positioning systemoutlined above. The frog central compute 1401 may be a piece ofelectronic hardware capable of all described inputs and processing alldata coming into, out of, and within the frog itself (e.g., functioningas the frog brain 605). An example of this processor may be a RaspberryPi 3 b+, among many other capable electronic hardware. The tool 1406 maybe the combination of elements being manipulated by the frog 600 suchas, in this example, the elevation mechanism and the module acquisitionsystem payload. The module acquisition system payload may include anorientation sensor [or IMU] on-board that may inform the frog about thestate of the payload bar during its performance of the directives. Ifthe payload bar is not at the desired orientation, it may be likely thata failure has occurred, so the frog may enter failure mode and analyzesthe root of the problem and decides the optimal next steps as describedabove. The x-drive 1403 and y-drive 1404 may drive the wheel assembliesthat actuate the frog along the “x” and “y” planes on top of the growthstructure as described above. Frog central compute 1401 may senddirectives to the x-drive 1403 and y-drive 1404 in the form of USBserial, for example, for the motor driver to convert into signals thatmay be sent to each motor and/or to have the encoder data returned forclosed-loop control. The frame shift 1405 may include the directionchange actuator that controls the direction of actuation along the railsystem as described above. Frog central compute 1401 may have thecapacity to add more components to add capabilities in order to achievevarious frog functions.

FIG. 15 shows an external controller 1500 according to an embodiment ofthe disclosure. The external controller 1500 may provide a wider systemthat the frog 600 may interact with and that may aid in the constructionand delivery of directives based upon a plethora of other data sources.The cloud-based software architecture 1502 may communicate withcomputational devices local to the facility, such as local DB 1501and/or controller 1500. The local DB 1501 may take information from thecloud-based software architecture 1502 and, potentially, input from theoperator on-site at the facility, then may send directives to the frogcontroller 1500. The frog controller 1500 may use this information todecide which frog 600 to send the lower-level, action-based directivesto the optimal frog for that scenario, as described above.

FIG. 16 shows a control system according to an embodiment of thedisclosure, illustrating a logical arrangement among software elementswithin controller 1500, local DB 1501, and/or cloud-based softwarearchitecture 1502.

Data from the facility 1601 may flow in through the ground controller1603 to the cloud-based software architecture. This data may passthrough a filtering and queuing engine 1604 before it is ingested 1605into various cloud-based services 1606. These services 1606 may storethe data in a number of different locations and forms for it to beretrieved through various querying methods. The cloud-based softwarearchitecture may also include plant recipes 1607 which may becontinuously optimized and/or iterated upon using machine learning,artificial intelligence, etc. Plant recipes 1607 may dictate theperformance of the subsystems within the facility. Comparing thereal-time state of the facility to the plant recipe requirements mayyield a difference. This difference may be actively minimized throughactuation of the various subsystems 1602 on the ground, such as frog(s),lighting, nutrients, HVAC, etc. Plant characteristics that manifest inthe various sensed environmental characteristics may be recorded,queried, and compared against the desired plant characteristics.Variations in outcome may be recorded, and algorithms may be executed onthose differences to further understand the plant's response to theenvironmental characteristics and improve the performance of the growthsystem.

The cloud-based scheduler 1608 may be responsible for taking the currentstate of the facility and directives coming from thecloud-infrastructure to dictate the performance of the actuators withinthe growth arena. Copies 1609 of this schedule may be brought down fromthe cloud-based software architecture 1606 such that any disconnectionfrom the internet may not result in the malfunction of the system. Thecontroller 1602 that is on-site within the facility may be responsiblefor turning those high-level directives into actuator state changes.With the number of variables and the complexity of the interactionsbetween many of these variables, the cloud-based scheduler 1608 may be asophisticated optimization algorithm that manages the performance of thefacility. Some embodiments may include a user interface 1610 allowingusers to monitor and/or provide input into any of the aforementioned,otherwise automated, systems.

System data stored in cloud-based services 1606 and/or used elsewherewithin the architecture may be represented as a set of objects in thesystem's computer knowledge base. The objects may represent any types ofobjects, both physical and conceptual, in the system. The objects may belinked to indicate various relations between the objects.

The “recipes” for growing plants may be objects, and the completerepresentation of biological entities (plants) in the indoor farm may beone or more objects. This may be in addition to representing thetraditional physical objects in the farm and facilities. This may allowthe systems, as described elsewhere herein, to compare the expectedstate of the biological entity (the plant's recipe) with the actualstate of the plants as perceived from the sensor data. Objects mayinclude information for each plant grown on the farm; recipes about howto grow each type of plant or species on the indoor farm; physicalobjects in the farm; and/or characteristics of the market in which thesystem is operating.

Some objects may be classified as essential objects. Examples mayinclude lights, nutrient system components, HVAC, etc. Plants may betheir own unique subclass of essential objects.

Some objects may be classified as structures. Examples may includecomponent units of the indoor farm such as walls, cavities, etc.

Some objects may be classified as equipment, such as frogs, pucks,combs, etc.

Some objects may be classified as facilities, which may representinformation about a physical indoor farm or growth area. Each separateindoor farm may be represented as a different object.

Some objects may be classified as variable history. Objects representinginformation about the history or time phased summary of an object may beexamples of variable histories.

Some objects may be classified as recipes.

The system may also define relationships between objects. There may bevarious types of relationships.

One example relationship may be a binary association. This link mayrepresent a one-to-one relationship between two objects. This mayindicate a physical relationship, such as each germination module havinga germination sensor. It may also represent a symbolic association, forexample, each plant may have a unique plant variable history associatedwith it.

One example relationship may be a class extension. This link mayrepresent the relationship between a primary component andsub-components or specialized components of that object. For example,different types of liquid and nutrient tanks may be class extensions ofthe “tank” class.

One example relationship may be a dependency. Some objects may beresults of “parent” objects. This may be used for sensor data, forexample. Data collect objects (e.g., an image or sensor reading) may be“dependent” upon the sensor (e.g., imaging system) that collects thatdata.

One example relationship may be an aggregation. These may be one-to-manyrelationships where objects may be grouped into another object. Forexample, plants may be aggregated into a growth module. Plants may alsobe aggregated or organizationally grouped into a species.

One example relationship may be a composition. This may representobjects that are components of another object. For example, the plantscience lab may be “composed” of (among other objects), an HVAC,germination unit, and PSL growth unit.

Some specific examples of information that may be related to otherinformation in this fashion may include, but are not limited to, thefollowing.

Each plant grown in the indoor farm may be represented as a separateobject. Each plant object may contain basic plant information such askey dates in plant's life such as planted (birth), germinated,transitions, harvested (death), etc. Each plant may be linked toinformation about that plant. This may include the plant's species, theplant's recipe, plant's physical location in the farm, the state of theplant at every stage of its life cycle (e.g., which may include sensordata as well as a representation of information about the plant that hasbeen extracted from the data and interpreted), and/or harvestinformation about when and how the plant was harvested.

Each recipe used in the indoor farm may be represented as a separateobject. A recipe may include a semantic representation of how a plantshould be grown. The recipe may predict through representational linksthe features a plant may exhibit through its lifecycle as well as theexpected outputs of the plant upon harvest. In this process, the recipesmay be used by system algorithms to compare expected plantcharacteristics to observed characteristics collected from the sensors,as noted above. Specific representations may include, but are notlimited to, Recipe ID (e.g., name, plant species/subspecies); theplant's growth plan that indicates how the plant should be grown andrepresents the actions taken on the plant; the type of lighting (e.g.,frequency spectrum, color) applied to the plant, when lighting wasapplied to the plant, the intensity of the lighting applied to theplant, and/or other details (e.g., distance from plant, angle, etc.);what nutrients are used to grow the plant and/or how often (frequency)and in what amounts were they applied; temperatures of plantenvironment; etc. Each recipe may have relationships to plants grownwith this recipe and/or species for which the recipe is derived.

Each facility may be represented as a separate object. Each facility maybe linked to its major equipment and components within the farm. Alsorepresented with each facility may be information about the name of thefarm, its physical location, the date it was put in service, its size(e.g., number of pods), etc.

The representations and links may enable the system to determineinformation such as crops grown, types of crops grown over time, recipesused, farm (location) results, harvests, harvest results (e.g., outputof various crops), quality outcome, revenue outcome, notes oranomalies/information to remember, other farm information, cost ofoperations, maintenance records, key personnel, notes or anomalies aboutfarm, etc.

Each piece of structure, equipment, and/or essential object in theindoor farm may be represented as a separate object. Theserepresentations may be classes for the physical inert objects foundwithin the indoor farm and facilities. Structures may be larger farmcomponents, such as the germination unit or a pod, as described below.Structures may be composed of other structures, equipment, or essentialobjects. Equipment and essential objects may represent physicalcomponents. Essential objects may represent equipment for which there isa dynamic history that may be represented. For example, an essentialobject may be an HVAC unit. As the HVAC unit operates, a variablehistory object (HVAC variables history) may be associated with the HVACto record information about its performance and operating history.Physical equipment that does not require the representation of dynamicinformation, such as a filter or several sensors, may be calledequipment, not an essential object. Structures, equipment, and essentialobjects may be linked through various one-to-one and one-to-manyrelationships as appropriate.

Variable history objects may be inherited classes of information thatmay be attached to another object representation in the system. Theserepresentations may include time linked information about their attachedobject. The variable history representation may be used for all types ofboth physical and conceptual representations in the system that mayrequire the system to collect data about or store information atdifferent points in time. For example, this can include collectedinformation about the biological entities (plants) in the system and/orinformation about physical objects such as a growth module.

FIG. 17 shows a rail structure 1700 according to an embodiment of thedisclosure. In some embodiments, the rail structure 1700 may be made of½ inch schedule 80 PVC pipe 1701 connected to 4-way PVC connectors 1702.In other embodiments, other rail objects may be used to form structure1700. The rail structure 1700 may mount to the top of the load beams inthe growth structure and may support one or more frogs 600. A pluralityof junctions may sit above a plurality of columns mounted to and hangingfrom the load beams. The alleyway 1703 may be a portion of the growthstructure which allows the frog 600 to pass between rows of pods. Thisalleyway 1703 may be built into the growth structure at some intervalalong the row of pods, for example: three 24ft uprights separating therows of pods, then an 18ft upright to allow the frog to pass betweenrows of pods.

The rail structure 1700 may be mounted on top of the entire growthstructure. This may give the frogs 600 access to the entire growth arenaand to the peripheral subsystems. As mentioned before, the railstructure 1700 may be mounted to the roof or mounted to anothersubstructure above the growth structure and may have a convex or concaveprofile or a flat surface for the robots to translate on top of.

FIG. 18 shows a rail structure junction according to an embodiment ofthe disclosure. The rail structure 1700 may include many repeatableunits called junctions 1801. These junctions 1801 may be mounted to thetop of the load beams that may be mounted to the uprights which may bebolted to the floor. These junctions 1801 may be situated centrallyabove the light columns that illuminate the growth modules/combs. Withthe shorter member of the junction 1801 mounted to the load beam and thelonger member of the junction 1801 mounted to the pallet support beams,the frog 600 may have full access to all of the components beneath it.In this instance, the long-member rail may be mounted to the top of thecavity. The fluidics system may be mounted to the same pallet supportbeam that the long-member rail is mounted to. In other instances, therail may be mounted to the light column pallet support beam. With thevolume and dimensions of the frog 600 varying with the function eachfrog 600 is built to perform, the frog 600 may always configure itselfaround the size and location of the junction implemented in thatfacility. Under some circumstance, junctions 1801 may be of varyingdimensions to accommodate various subsystems.

FIG. 19 shows a connector according to an embodiment of the disclosure.The connector 1902 may act as the connecting point between pipes (e.g.,1701) making up some portion of the rail structure. In this example, theconnector 1902 is a four-way PVC connector linking four PVC pipes,though other embodiments may have different arrangements. The junctionmay be designed in such a way that the convex wheels of the frog 600 mayseamlessly transition from the PVC rail 1901 to the 4-way PVC connector1902 and back to the PVC rail 1901. The cutout 1903 may provide not onlya potential mounting point of the rail structure to the load beam, butalso something that the frog 600 may utilize for fine localization. Thiscutout 1903 may be empty, with the frog 600 being able to identify itusing various methods, or the cutout 1903 may have an indicator of somekind that may alert the frog 600 that it has reached the correctlocation above junction.

FIG. 20 shows a frog 600 and junction 2001 according to an embodiment ofthe disclosure. The frog 600 may properly align itself over a junction2001. The frog 600 may the inner/outer frame such that all wheels1203/1204 are level and planted on the desired junction 2001. The frog600 channels may now be aligned with the column channels in order of thefrog 600 to perform a task (e.g., a module acquisition). In this case,the light column is bi-directional with both led strips [illuminationboth adjacent columns], though, in other cases, the light columns may besplit into two, with two separate pallet support beams so that the frog600 can perform light movement and light removal/replacement.

Once the module acquisition has been performed, the frog 600 may eitherelevate or lower the outer frame to travel to its next predeterminedlocation. This combination of columns, junctions, light columns, andgrowth modules may repeat throughout the growth arena, with the frog 600having the capacity to locate any component within the facility. Everycomponent within the facility may have its location known in thedatabase, so the frog 600 may understand exactly which junction it mustrelocate to in order to access a target component.

FIG. 21 shows an electrical configuration of a power distribution systemaccording to an embodiment of the disclosure. This may include acollection of components responsible for bringing power in from anexternal power source [e.g., the grid, renewable energy sources,non-renewable energy sources, etc.] and manipulating it before deliveryto the various components and subsystems within the facility that mayrequire power. This power distribution system may frequency modulate thepower entering the lights, control intensity of illumination, andcontrol the output spectrum of the LED lights. This power distributionsystem may also accommodate energy coming directly from solar powerwithout battery storage.

For the fluidics system 2102, the 120-volt alternating current (AVC)line may enter an uninterruptable power supply (UPS) 2101. This UPS 2101may serve as a battery backup and power regulator for the fluidicssystem 2102. The UPS 2101 may send power to a variety of voltageconverters that step the voltage down to the required level to operatethe subcomponents. If additional pods are introduced into the system,extra components may be added to accommodate.

For the light controller 2103, a 277 VAC line may be brought in tosupply enough energy to however many pods are present. In this example,3 pods are present, therefore the power is sent to three different lightcontroller modules. Other subsystems within the facility [HVACcompressor 2105, HVAC circulation 2106, frog charge/transmit 2104,control center, preprocessing and postprocessing, etc.] also may receivepower to operate.

FIG. 22 shows a light controller 2200 according to an embodiment of thedisclosure. The example light controller 2200 may include the hardwareand circuit setup for a set of two pods, but any number of pods may bepresent. For power from the grid 2201, an alternating currentsolid-state relay (AC SSR) 2202 may sit between the grid 2201 and therectifier 2203. In the case of a renewable energy source 2204, a directcurrent solid state relay (DC SSR) 2205 may feed directly into the “highline” with a fuse 2206 downstream to protect the light circuit. Thepower may be routed through each respective light column 2207—six inthis case—then brought through high-power MOSFETs 2208 before enteringhigh voltage ground (HVG) 2209. The 277 VAC may be converted 2210 to 12volts direct current (VDC) to supply various electrical components 2211that may pulse-width modulate (PWM) the signal going to the lightcolumns 2207.

This arrangement of electronic hardware may allow for minimal electricalcomponents between the lights and the grid whilst also improving thepower factor, drastically decreasing the cost of power delivery to theLED strips, and providing decreased maintenance cost since LED driversmay fail regularly. This implementation may centralize the powerdelivery hardware outside of the growth arena, which may decrease heatproduction within the growth arena and/or improve the serviceability ofthe system through easier access to the hardware.

FIG. 23 shows a pre-pod fluidics system 2300 according to an embodimentof the disclosure. The fluid in the pre-pod fluidics system 2300 mayflow from right-to-left in this illustration. An array of pumps 2301 maydraw nutrient mixture in from one or many nutrient tanks that may begenerally premixed. The premixing may be performed by a closed loopsystem of nutrient-characteristic sensors and peristaltic pumps tocontrol the nutrient characteristics inside the tanks. In addition tothe nutrient lines, a clean-water line (e.g., by reverse osmosis) and/orwash line 2302 may connect in parallel to the feed line. These lines maybe used for flushing and cleaning of all the components downstream,including the cavities and the drain line.

An accumulation tank 2303 may be used to mitigate the water hammercaused by cycling pumps which may damage sensor components. Moreover,the accumulation tank 2303 may help with maintenance of a constantpressure in the system. A variety of valves, filters, risers, gages,sensors, regulators, and couples 2304 may be used to maintain adesirable state in the pre-pod fluidics system. As the fluids are aboutto introduced to the pods, a set of manual valves and electronicallycontrolled valves 2305 may regulate the flow timing of nutrient deliveryto the plants.

FIG. 24 shows a pod fluidics system 2400 according to an embodiment ofthe disclosure. This system may be disposed within the column's cavity(e.g., 309 and 312). Here, fluid introduced from the bottom of thecolumn's cavity may travel up a central conduit to the top of thecolumn. It then may split into two channels that break off into anynumber of vertically hanging fluid-delivery lines. Connected to thesemay be vertically hanging nozzles. These nozzles may atomize the fluidand/or may spray it into the column's cavity. Generally, a higherdensity of nozzles may be situated at the top of the column's cavity ascompared to the bottom of the column. The goal of these fluidics linesmay be to cover the entire surface-area of every root within thecolumn's cavity.

From the accumulation tank 2405, the fluid may enter the distributionlines and may come into contact with the electronically controlledsolenoid valves 2402 first, then the manually controlled valve 2401. Thefluid may then enter the feed line to the column. In this image, fourpods have had their fluidics system routed. The column's fluidicsintroduction point 2404 may feed the pressurized nutrient [or other]fluid to the column to distribute to the plants through the nozzles.

After the optimal amount of fluid has been deposited inside the column,the remaining liquid may drain back down to the drainage tray and may beremoved by drain bulkhead connection 2405 to be accumulated back intothe drain tank 2406. This fluid may be tested and recycled back into thenutrient tanks to flow back into the system.

The fluidics system may be built to auto-clean. Upstream of the nozzlesthere may be a cleaning solution being stored in a container. Scheduledby the central control system, at various points in time, the cleaningsolution may be introduced to the system and flowed through the pumps,manifolds, valves, junctions, connectors, pipes, and nozzles to removeunwanted biological material among other things. This cleaning solutionmay be used not only to clean the nozzles in the column's cavity, it mayalso be used to clean the column's cavity itself. The solution may besprayed into the column's cavity to neutralize unwanted biologicalgrowth. This spoiled cleaning solution may be sent through the drainagesystem to be disposed in accordance with the presiding regulations.

FIG. 25 shows a light column 2500 according to an embodiment of thedisclosure. The illumination system may be primarily responsible for thedelivery of photons of the correct wavelength, intensity and density tothe biological matter within the facility. The light column 2500 may bea subsystem of the illumination system that may interact with the growthstructure, power distribution system, HVAC system, and/or frog tomaintain optimal illumination of the biological entities.

The light column may be suspended from a pallet support beam 2501 at thetop of the light column that may be seated on the load beams spanningbetween uprights. The light column may be connected electrically to thepod light controller at either the top or the bottom of the lightcolumn. The connection may be wired, contact, or blind-mate connections,for example.

In this instance, two straps hang down from the frame at the top. Thesestraps may be folded and holed such that the wires can travel down theinterior of the crease and the lights can be mounted at different pointsalong the straps. For this example, LED strips 2502 may be used toilluminate the biological entities. The LED strips may be mounted to thestraps and may receive power from the wires confined in the fold of thestraps. In other iterations of the light column, the LED strips may beoriented vertically or diagonally with the straps being on the ends,central, or any variation in between. Another potential implementationof the light column may take notions from the cavity channel interactionwith the growth module/comb; two channels per light column may hang fromthe load beams on the growth structure. Light strips/modules may then bedropped down into the channel and may receive power upon contact ofeither the terminals of the lighting module below, or from the terminalshoused within the channel.

The light column may be constructed in such a way that it may be movedcloser or further away from the growth modules/comb it is illuminatingor removed from the growth arena altogether. When repositioning thelight column, the frog may lift the pallet support beam up from the loadbeam and reposition it to maintain optimal illumination of thebiological entity in terms of plant characteristics and operationalefficiency.

The frog may be responsible for the removal of the light columnaltogether. If there is a wired connection, the connector may bedisengaged manually or through a frog subsystem. Once the connection tothe power distribution system is unmated, the frog may roll-up, fold, orstack the lights within its inner frame in order to move the lightcolumn to another location within or outside of the growth arena.

FIG. 26 shows an HVAC system 2600 with a growth structure according toan embodiment of the disclosure. HVAC system 2600 may control theatmospheric elements of the environmental characteristics within thefacility. On the back-end a collection of hardware and software maytreat the air so that it enters the inlet duct 2603 at the desiredtemperature, humidity, CO2 concentration, O2 concentration, andvolumetric flow rate, among other parameters. This inlet duct may splitinto ducts oriented upward and downward at each pod such that the newair can be delivered either side of each column. A variety of componentsthat may include HVAC junctions, fittings, elbows, reducers, couplers,and/or splitters may be used to redirect the flow of air into thedesired locations within the growth arena. After the main inlet duct hasbeen split to each of the growth pods, an elbow 2604 may redirect theflow from outside the growth arena to inside the growth arena. At thispoint the air may enter into a rectangular profile that may be optimizedfor ducting through the growth structure and may flow through thisrectangular-profiled duct to the point of delivery. Along thisrectangular-profiled duct there may be a variety of diffusers 2602,emitters, nozzles, and orifices that may deliver the treated air to thecavities 2605. Once the air has been delivered to the growth arena, theair may heat up and rise to the top of the growth arena, at which pointthe outlet duct 2601 may remove the air.

FIG. 27 shows an HVAC system 2600 with no growth structure according toan embodiment of the disclosure. The air may be delivered to the sharedatmospheric zones between the columns in the growth pods and/or to theatmospheric zones at either end of the growth pods. Air may be deliveredto the bottom of the column and, using the effects of natural convectionand the entrance velocity of the air, it may travel upward, generating aflow of air from the bottom of the column to the top of the column. Avarying number of rectangular-profiled ducts may be introduced atvarious heights along the column to make sure that the environmentalcharacteristics across the column are as uniform as possible whilemaintaining the flow of air from low to high. To help with this,diffusers 2703 may be installed in various places downstream of theinlet duct 2702.

Additional factors to consider may include the impact of the lights onthe atmospheric environment. The lights within the atmospheric zonebetween the columns may heat up the air. As is well known, hot airrises, which may assist in the movement of air from the bottom of thecolumn to the top of the column. Vertical-plane production may enablenatural convection which produces the effect of airflow beneath thecanopy of the crop. In horizontal-plane production, stagnant air mayaccumulate beneath the canopy, which may increase dead-zones, moisturebuild-up, and, inevitably, undesirable biological growth.

Once the newly-introduced air has performed its duty within theatmospheric zone, it may rise naturally above the growth structure wherethe frog is operating. Part of the benefit of a top-mounted automationmechanism is this unoccupied volume above the growth structure. Here,unwanted heat and used air may accumulate and not adversely affect thebiological entities in the columns. An outlet duct 2701, which may aidin the flow of air from low to high, situated at the edge of the growtharena may pull air directly out of the frog's operating volume above thegrowth structure.

This HVAC ecosystem may have many variations in implementation but maybe built to implement the following overriding assumptions: maintain aflow of air from the bottom of the column (growth structure) to the topof the column (growth structure); maintain environmental characteristicsthat are favorable to the biological entity growing within the growtharena that each HVAC system is delivering and removing to/from; andinteract with the facility software control system to optimizeperformance in conjunction with other subsystems within the facility(fluidics, lighting, frog, etc.).

While various embodiments have been described above, it should beunderstood that they have been presented by way of example and notlimitation. It will be apparent to persons skilled in the relevantart(s) that various changes in form and detail can be made thereinwithout departing from the spirit and scope. In fact, after reading theabove description, it will be apparent to one skilled in the relevantart(s) how to implement alternative embodiments. For example, othersteps may be provided, or steps may be eliminated, from the describedflows, and other components may be added to, or removed from, thedescribed systems. Accordingly, other implementations are within thescope of the following claims.

In addition, it should be understood that any figures which highlightthe functionality and advantages are presented for example purposesonly. The disclosed methodology and system are each sufficientlyflexible and configurable such that they may be utilized in ways otherthan that shown.

Although the term “at least one” may often be used in the specification,claims and drawings, the terms “a”, “an”, “the”, “said”, etc. alsosignify “at least one” or “the at least one” in the specification,claims and drawings.

Finally, it is the applicant's intent that only claims that include theexpress language “means for” or “step for” be interpreted under 35U.S.C. 112(f). Claims that do not expressly include the phrase “meansfor” or “step for” are not to be interpreted under 35 U.S.C. 112(f).

What is claimed is:
 1. An automated robotic device configured to operatewithin an automatic vertical farming system, the device comprising: aframe; one or more wheels coupled to the frame and configured to engagewith and traverse a top side of a farm facility frame defining at leastone growth area and configured to support a plurality of vertical plantgrowth structures within the at least one growth area, wherein the topside of the frame is above the at least one growth area and the robot ismovably supported so that it is movable above the at least one growtharea; a propulsion system configured to drive at least one of the wheelsand thereby cause the robotic device to traverse the farm facilityframe; at least one tool configured to manipulate the plurality ofvertical plant growth structures; and a control system configured toautomatically control movement of the robotic device and operation ofthe at least one tool.
 2. The device of claim 1, wherein the at leastone tool includes at least one tool payload configured to be removablycoupled to the robotic device.
 3. The device of claim 1, wherein the atleast one tool includes a gripping tool payload configured to grip,raise, lower, and release at least one of a plurality of growth modules.4. The device of claim 1, wherein the at least one tool includes atleast one sensor payload configured to gather data within the at leastone growth area.
 5. The device of claim 4, wherein the control system isconfigured to send the data to at least one external computing devicenot on board the robot.
 6. The device of claim 4, wherein the at leastone sensor payload includes at least one of the following: amultispectral camera, a hyperspectral camera, a monospectral camera, anIR camera, a CO2 sensor, an O2 sensor, a humidity sensor, an airflowsensor, an audio spectrum sensor, an inertial measurement unit sensor, atemperature sensor, a barometric sensor, a turbidity sensor, a movementsensor, a light sensor, a distance sensor, a LiDAR sensor, and a powerlaser.
 7. The device of claim 1, wherein the at least one tool includesa cleaning payload configured to sanitize the at least one growth area,remove debris from within the at least one growth area, or a combinationthereof.
 8. The device of claim 1, wherein the at least one toolincludes a seeding payload configured to place seeds into a growthmedium located in the at least one growth area.
 9. The device of claim1, wherein the at least one tool includes a light movement payloadconfigured to move light elements into, out of, and within the at leastone growth area.
 10. The device of claim 1, wherein the at least onetool includes a trimming payload configured to trim plant roots, plantshoots, or a combination thereof within the at least one growth area.11. The device of claim 1, wherein the at least one tool includes apollinating payload configured to remotely pollinate plants in the atleast one growth area.
 12. The device of claim 1, wherein the at leastone tool includes a harvesting payload configured to harvest plants,excise parts of plants, or a combination thereof within the at least onegrowth area.
 13. The device of claim 1, wherein the control systemincludes: a camera configured to capture image data of an environmentsurrounding the robotic device; and a processor in communication withthe camera configured to detect fiducial features within the image dataand determine a location of the robotic device from the fiducialmarkings based on stored information defining known locations of thefiducial features .
 14. The device of claim 13, wherein the processor isfurther configured to generate the stored information by controlling themovement of the robotic device in a stepwise fashion and, at each step,recording locations of imaged fiducial markings to form a map of theenvironment.
 15. The device of claim 1, wherein the control systemincludes: at least one hall effect sensor configured to capture magneticfield data of an environment surrounding the robotic device; and aprocessor in communication with the at least one hall effect sensorconfigured to detect a signature or reference magnetic flux or spatialdistribution of magnetic flux from at least one magnet in at least onedefined location, detect and count a number of encoder-counts past thesignature or reference magnetic flux or spatial distribution of magneticflux that are traversed by the robotic device as it moves, and determinefrom the count a position of the robotic device relative to the at leastone magnet.
 16. The device of claim 1, wherein the one or more wheelsare configured to be raised and lowered, and the control system isconfigured to control raising and lowering of the one or more wheels.17. The device of claim 16, wherein the control system is configured tocontrol the raising and lowering using one or more direction changeactuators.
 18. An automatic vertical farming system comprising: therobotic device of claim 1; and the farm facility frame, wherein the farmfacility frame comprises one or more rail tracks on the top side of thefarm facility frame configured to engage with the one or more wheels.19. The system of claim 18, wherein the one or more rail tracks includeat least one rail track arranged in an X direction and at least one railtrack arranged in a Y direction.
 20. The system of claim 19, wherein theat least one rail track arranged in the X direction and the at least onerail track arranged in the Y direction are co-planar and perpendicularto one another.
 21. A method of controlling an automated robotic deviceconfigured to operate within an automatic vertical farming system, themethod comprising: automatically controlling, by a control system of therobotic device, a propulsion system to drive at least one of one or morewheels coupled to a frame and thereby cause the robotic device totraverse a top side of a farm facility frame defining at least onegrowth area and configured to support a plurality of vertical plantgrowth structures within the at least one growth area, wherein the topside of the frame is above the at least one growth area and the robot ismovably supported so that it is movable above the at least one growtharea; and automatically controlling, by the control system, operation ofat least one tool configured to manipulate the plurality of verticalplant growth structures.
 22. The method of claim 21, whereinautomatically controlling the at least one tool includes causing agripping tool payload to grip, raise, lower, and release at least one ofa plurality of growth modules.
 23. The method of claim 21, whereinautomatically controlling the at least one tool includes causing atleast one sensor payload to gather data within the at least one growtharea.
 24. The method of claim 23, further comprising sending, by thecontrol system, the data to at least one external computing device noton board the robot.
 25. The method of claim 21, wherein automaticallycontrolling the at least one tool includes causing a cleaning payload tosanitize the at least one growth area, remove debris from within the atleast one growth area, or a combination thereof.
 26. The method of claim21, wherein automatically controlling the at least one tool includescausing a seeding payload to place seeds into a growth medium located inthe at least one growth area.
 27. The method of claim 21, whereinautomatically controlling the at least one tool includes causing a lightmovement payload to move light elements into, out of, and within the atleast one growth area.
 28. The method of claim 21, wherein automaticallycontrolling the at least one tool includes causing a trimming payload totrim plant roots, plant shoots, or a combination thereof within the atleast one growth area.
 29. The method of claim 21, wherein automaticallycontrolling the at least one tool includes causing a pollinating payloadto remotely pollinate plants in the at least one growth area.
 30. Themethod of claim 21, wherein automatically controlling the at least onetool includes causing a harvesting payload to harvest plants, exciseparts of plants, or a combination thereof within the at least one growtharea.
 31. The method of claim 21, further comprising: capturing, by acamera, image data of an environment surrounding the robotic device;detecting, by the control system, fiducial features within the imagedata; and determining, by the control system, a location of the roboticdevice from the fiducial markings based on stored information definingknown locations of the fiducial markings.
 32. The method of claim 31,further comprising generating, by the control system, the storedinformation by controlling the movement of the robotic device in astepwise fashion and, at each step, recording locations of imagedfiducial markings to form a map of the environment.
 33. The method ofclaim 21, further comprising: capturing, by at least one hall effectsensor, magnetic field data of an environment surrounding the roboticdevice; detecting, by the control system, a signature or referencemagnetic flux or spatial distribution of magnetic flux from at least onemagnet in at least one defined location; detecting and counting, by thecontrol system, a number of encoder-counts past the signature orreference magnetic flux or spatial distribution of magnetic flux thatare traversed by the robotic device as it moves; and determining fromthe count, by the control system, a position of the robotic devicerelative to the at least one magnet.
 34. The method of claim 21, furthercomprising controlling, by the control system, raising and lowering ofthe one or more wheels.